AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Home Food Science Article
PDF (3.5 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Publishing Language: Chinese | Open Access

Authenticity Identification of Geographical Indication Mutton Based on Mineral Element Fingerprint

Jing QI Yingying LI ( )Rui JIANGChen ZHANGShunliang ZHANGWenping GUOShouwei WANG
Beijing Key Laboratory of Meat Processing Technology, China Meat Research Center, Beijing 100068, China
Show Author Information

Abstract

This study proposed a technique for identifying the authenticity of geographic indication mutton based on mineral element fingerprint combined with one-class modeling strategy. The results showed that the contents of mineral elements in the meat of Yanchi Tan sheep, Balikun Kazak sheep and Sunit sheep under the protection of geographical indication had fingerprint characteristics. In the one-class modeling strategy, only real sample sets were collected for modeling to identify the real samples from a variety of fraud samples. The soft independent modeling of class analogy (SIMCA) model based on each of the geographical indication mutton samples had excellent performance, with an identification accuracy of 100% for the test samples. Therefore, mineral element fingerprint combined with one-class modeling has a wide application prospect in the field of authenticity identification of geographical indication mutton.

CLC number: TS207.7 Document code: A Article ID: 1002-6630(2022)24-0365-06

References

【1】
【1】
 
 
Food Science
Pages 365-370

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
QI J, LI Y, JIANG R, et al. Authenticity Identification of Geographical Indication Mutton Based on Mineral Element Fingerprint. Food Science, 2022, 43(24): 365-370. https://doi.org/10.7506/spkx1002-6630-20220227-237

291

Views

0

Downloads

0

Crossref

0

Scopus

0

CSCD

Received: 27 February 2022
Published: 25 December 2022
© Beijing Academy of Food Sciences 2022.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).